For abnormality diagnosis of rotating machines, due to the superior diagnostic accuracy, judgment by signals detecting vibration of the bearings (hereinafter referred to as “vibration diagnosis”) is generally used. This method measures the impact vibration which occurs proportionally to the rotational speed and enables identification of abnormal portions from the intervals of the impact vibration.
However, in general, in the case of 100 rpm or less low speed rotating machines, the vibration occurring along with bearing abnormalities is small and the intervals of occurrence of impact vibration also become longer, so diagnosis has been considered difficult. In particular, in a case of several rpm, very low speed rotating facilities such as the rolls of continuous casting machines, differentiation of signals accompanying abnormalities and noise is difficult and high accurate diagnosis has been impossible.
To improve the accuracy of diagnosis of bearings of such low speed rotating machines, for example, Japanese Patent Publication (A) No. 3-245054 proposes to detect an AE (acoustic emission) signal emitted by bearings, calculate the duration by which the AE signal exceeds a reference value, and judge there is an abnormality when this duration exceeds another reference value.
Further, Japanese Patent Publication (A) No. 7-270228 proposes to use an acceleration sensor to detect bearing vibration, filter the detected signal by a bandpass filter, then process it by envelope processing, compute a difference between a largest value and smallest value of the waveform signal obtained in a predetermined time interval, and judge there is an abnormality when this difference exceeds a threshold value given in advance so as to thereby automatically diagnosis abnormalities of a low speed rotating machine.
Further, Japanese Patent Publication (A) No. 10-160638 proposes a method of using an acceleration sensor to detect bearing vibration, obtain output of a predetermined value or less from that detected signal by a low pass filter, process this by multiplying it by an odd number of 3 or more, and compare this waveform with a reference value set in advance so as to judge if there is an abnormality.